I applied through a recruiter. I interviewed at Andersen Lab (Tbilisi) in Mar 2026
Interview
The interviewer conducted the session in a very mechanical manner, strictly following a script and often reading questions and descriptions verbatim.
Hiring process consists of three stages: an initial HR interview, followed by an AI-based interview conducted on the Andersen side, and finally technical interview with the client.
The following HR questions were asked:
Why are you considering a job change?
What are your top three criteria when evaluating a job offer?
Do you currently have any offers under consideration?
Are there any domains you prefer not to work in ?
The second stage involved an AI-driven interview. The experience was poorly designed: candidates are required to verbally dictate their answers to an AI system, which makes the process uncomfortable and inefficient.
3
Other Senior Java Developer Interview Reviews for Andersen Lab
I applied online. The process took 1 week. I interviewed at Andersen Lab (Bengaluru) in Mar 2025
Interview
Applied through Naukri.com and received an email within a week to take an online assessment test on Recruiter.ai.
It was like 30 questions will display one-by-one on screen and we have to answer all of those or skip if you want. We have 1:30 min for each question.
I have given most of the answers (~25) correct but still received email that not selected. I think we just need to say some keywords related to the answer as at the end it is AI who is review our answers and decide that you're selected or not. 😒
Interview questions [3]
Question 1
Q1. What is the difference between strong, weak and soft references in Java?
Q2. What is the role of the volatile keyword in Java and how does it work?
Q3. How do you implement pagination in SQL queries?
Q4. Discuss how security can be maintained in a serverless architecture.
Q5. How can caching improve application performance and what are some strategies to implement it?
Q6. What is the difference between synchronous and asynchronous communication between microservices?
Q7. What are the challenges of achieving data consistency in distributed systems and how to resolve those?
Q8. What are the advantages of using Docker for application deployment?
Q9. What are some common use cases for the Executor framework in Java?
Q10. What are the benefits of using functional interfaces and Lambdas in Java?
Q11. Can you explain the role of the Command pattern in software design?
Q12. How does the Spring Framework support dependency injection?
Q13. What is the purpose of the Java Memory Model (JMM)?
Q14. Can you explain the key concepts behind an Event-Driven Architecture and its use cases?
Q15. What is the role of reactive programming in Java and how is it implemented using Spring Reactor?
Q16. What is the role of annotations in Java EE applications?
Q17. How is dependency injection implemented in Spring Boot applications?
Q18. What are the key differences between SQL and NoSQL databases?
Q19. What is the difference between a HashMap and ConcurrentHashMap?
Q20. How do you handle versioning in RESTful APIs?
Q21. What is the role of Docker Compose in containerized applications?
Q22. Can you explain the concept of HATEOS (Hypermedia as the Engine of Application State) in the context of REST APIs?
Q23. Can you explain the role and benefits of the CyclicBarrer class in java and provide examples of its typical use cases?
Q24. How can you ensure that a Spring Data JPA application is optimized for performance?
Q25. What are some best practices for RESTful API design?
Code:
Q2. Practical Task: Design a Distributed Message Queue
You are tasked with designing and implementing a distributed message queue in Java. This message queue must support the following features:
1. Producer/Consumer Pattern: Multiple producers should be able to add messages, and multiple consumers should be able to consume messages concurrently.
2. Message Ordering: Ensure that the messages are consumed in the order they were produced, but only once.
3. High Availability: Implement fault tolerance mechanisms to ensure messages are not lost if a node in the system fails.
4. Scalability: The system should handle a large number of producers and consumers without severe performance degradation.
Provide a high-level implementation of the core components (e.g., Producer, Consumer, Broker) and explain the design decisions you made (e.g., thread safety, use of data structures, and synchronization mechanisms)
Code:
Q1. Design and implement a distributed cache system in Java, capable of handling high-throughput read and write requests across multiple nodes. The goal is to ensure data consistency and fault tolerance in case of node failures. Implement the following features:
1. Data Partitioning: Use consistent hashing to distribute data across multiple cache nodes.
2. Fault Tolerance: When a node fails, ensure that its data is redistributed to other nodes without losing information.
3. Read and Write Operations: Provide efficient APIs for put(key, value) and get(key) operations.
4. Concurrency: Ensure thread-safe operations for the cache.
5. Scalability: Allow dynamic addition and removal of nodes without affecting system performance.
Constraints:
• Implement the solution in a single Java class for simplicity.
• Do not use third-party libraries for consistent hashing.
Deliverables:
• A working Java implementation of the distributed cache.
• Explanation of your design decisions, including trade-offs.
